Abstract

AbstractSynapse strength can be modified in an activity dependent manner, in which the temporal relationship between pre- and post-synaptic spikes plays a major role. This spike timing dependent plasticity (STDP) has profound implications in neural coding, computation and functionality, and this line of research is booming in recent years. Many functional roles of STDP have been put forward. Because the STDP learning curve is strongly nonlinear, initial state may have great impacts on the eventual state of the system. However, this feature has not been explored before. This paper proposes two possible functional roles of STDP by considering the influence of initial state in modeling studies. First, STDP could lead to phase-dependent synaptic modification that have been reported in experiments. Second, rather than leading to a fixed phase relation between pre- and post-synaptic neurons, STDP that includes suppression between the effects of spike pairs lead to a distributed entrained phase which also depend on the initial relative phase. This simple mechanism is proposed here to have the ability to organize temporal firing pattern into dynamic cell assemblies in a probabilistic manner and cause cell assemblies to update in a deterministic manner. It has been demonstrated that olfactory system in locust, and even other sensory systems, adopts the strategy of combining probabilistic cell assemblies with their deterministic update to encode information. These results suggest that STDP rule is a potentially powerful mechanism by which higher network functions emerge.

Highlights

  • Synapse strength can be modified in an activity dependent manner, in which the temporal relationship between pre- and post-synaptic spikes plays a major role

  • I present two possible consequences of spike timing dependent plasticity (STDP) : initial relative phase dependent probabilistic frequency synchronization, which could result in phase-dependent LTP/LTD, and initial relative phase dependent entrained phase, which could lead to formation of probabilistic cell assemblies and cause deterministic updates between them

  • This paper presents an effort to study the influence of initial state in STDP, by numerically investigating a simple system which consists of an excitatory STDP synapse and two repetitive firing neurons with different autonomous period

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Summary

Introduction

Synapse strength can be modified in an activity dependent manner, in which the temporal relationship between pre- and post-synaptic spikes plays a major role. Rather than leading to a fixed phase relation between pre- and post-synaptic neurons, STDP that includes suppression between the effects of spike pairs [3] lead to a distributed entrained phase which depend on the initial relative phase This simple mechanism is proposed here to have the ability to organize temporal firing pattern into dynamic cell assemblies in a probabilistic manner and cause cell assemblies to update in a deterministic manner. It has been demonstrated that olfactory system in locust, and even other sensory systems, adopts the strategy of combining probabilistic cell assemblies with their deterministic update to encode information These results suggest that STDP rule is a potentially powerful mechanism by which higher network functions emerge. It is reasonable and meaningful to ask whether and, if yes, how, initial state of a STDP system would have great impacts on the eventual state of the system

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